Benchmark resources usage
Project description
Monitor Process Resources Usage
Bench aims to be a handy tool with these functions:
- Monitor CPU time (user time, sys time, real time)
- Monitor memory usage (vms usage, rss usage)
- Output to TSV(tab-delimited files)
- Output benchmarking metrics
- Visualize benchmarking over time
Examples
We showed several examples below. Please note that all output are tabularized manually.
Example 1: simple command
$> monitor.py sleep 2pid ppid utime stime rtime rss vms maxRss maxVms avgRss avgVms cwd cmd133692 133675 0.0 0.0 1.9368159771 774144 6066176 774144 6066176 774144.0 6066176.0 /home/zhanxw/mycode/bench/scripts sleep 2Example 2: complex shell commands with samping interval equaing 0.5 second
$> monitor.py sh -c ‘sleep 2 & sleep 4 & seq 1000000 >/dev/null & wait’pid ppid utime stime rtime rss vms maxRss maxVms avgRss avgVms cwd cmd135004 134985 0.0 0.0 3.9532430172 798720 4558848 798720 4558848 798720.0 4558848.0 /home/zhanxw/mycode/bench/scripts sh -c sleep 2 & sleep 4 & seq 10000000 >/dev/null & wait135006 135004 0.0 0.0 3.95348381996 655360 6066176 655360 6066176 655360.0 6066176.0 /home/zhanxw/mycode/bench/scripts sleep 4135005 135004 0.0 0.0 1.83160495758 774144 6066176 774144 6066176 774144.0 6066176.0 /home/zhanxw/mycode/bench/scripts sleep 2135007 135004 0.05 0.0 0.0599648952484 720896 6090752 720896 6090752 720896.0 6090752.0 /home/zhanxw/mycode/bench/scripts seq 10000000Example 3: generate benmarking metrics to external file
The small program, burnCpu, will keep CPU running for several seconds. Its source code is under src/.
$> monitor.py -t -o burnCpu ./burnCpu pid ppid utime stime rtime rss vms cwd cmd 135471 135454 0.04 0.0 0.0441780090332 1449984 12984320 /home/zhanxw/mycode/bench/scripts ../src/burnCpu 135471 135454 0.2 0.0 0.205282926559 1449984 12984320 /home/zhanxw/mycode/bench/scripts ../src/burnCpu 135471 135454 0.38 0.0 0.381079912186 1449984 12984320 /home/zhanxw/mycode/bench/scripts ../src/burnCpu ...
Additional result are stored in burnCpu.csv, burnCpu.trace.csv in the Comma-separated format (CSV).
burnCpu.csv content
pid,ppid,utime,stime,rtime,rss,vms,maxRss,maxVms,avgRss,avgVms,cwd,cmd 144433,144416,5.4,0.0,5.40555810928,1404928,12984320,1404928,12984320,1404928.0,12984320.0,/home/zhanxw/mycode/bench/scripts,../src/burnCpu
burnCpu.trace.csv content
pid,ppid,utime,stime,rtime,rss,vms,cwd,cmd 144433,144416,0.03,0.0,0.0423669815063,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu 144433,144416,0.19,0.0,0.20046210289,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu 144433,144416,0.36,0.0,0.373480081558,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu ...
By using the trace output file, burnCpu.trace.csv, you can draw benchmarking graphs, such as:
Notes
Shell (/bin/sh) can be used to execute commands. You can use “sh -c
‘command arg1 arg2 … ‘” (see Example 2).
Bench requires psutil to
collect basic benchmarking metrics, and
requires numpy and pandas for statistical calculations. We used psutil
version 3.1.1 in development.
Contact
Xiaowei Zhan<zhanxw[at]gmail.com
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